The long term goal of this proposal is to better understand how humans process sounds that change with time. The specific objective is to evaluate three models of sinusoidal-amplitude-modulation (SAM) processing: the low-pass filter model, the autocorrelation model, and the modulation-filterbank model. Assumptions made by each of these models on two key aspects of SAM processing will be tested: the processing of SAM in different spectral regions, and the processing of SAM of different rates. These assumptions will be tested by training listeners on SAM-rate-discrimination and SAM-detection tasks in separate experiments, and observing whether learning on the trained task with the trained sound subsequently influences, or generalizes to, performance on either the trained task with untrained sounds, or on untrained tasks with the trained sound. This project will provide a valuable test of the assumptions of these three models. It will also aid the development of training regimes for individuals with difficulty discriminating or detecting SAM, such as the hearing impaired.